Method of optimizing healthcare services consumption

ABSTRACT

A method of optimizing healthcare services consumption according to the invention includes the steps of assessing the healthcare situation of an employer providing healthcare benefits to a population, identifying a first group of patients from the population likely to generate expensive healthcare claims based on data representing past claims, periodically determining whether patients in the first group have satisfied certain predetermined healthcare requirements, identifying a first group of providers who provide high quality, cost efficient healthcare services based on the practice patterns of the providers, prompting patients who have not satisfied the predetermined healthcare requirements to obtain services from providers in the first group, and responding to healthcare requests from patients by determining whether the requesting patient is seeking services from a provider in the first group, and, if not, urging the patient to obtain such services from a provider in the first group.

RELATED APPLICATION

This application is a continuation of and claims priority to U.S. patentapplication Ser. No. 13/178,174, filed Jul. 7, 2011 entitled “Method ofOptimizing Healthcare Services Consumption,” which is a continuation ofU.S. patent application Ser. No. 12/773,334, filed May 4, 2010, now U.S.Pat. No. 8,036,916 entitled “Method of Optimizing Healthcare ServicesConsumption,” which is a continuation of U.S. patent application Ser.No. 10/313,370, filed Dec. 6, 2002, now U.S. Pat. No. 7,711,577 entitled“Method of Optimizing Healthcare Services Consumption,” the entiredisclosures of which are expressly incorporated herein by reference.

FIELD OF THE INVENTION

The present invention generally relates to a method of optimizinghealthcare services consumed by patients including employees and theirfamily members by improving the overall quality of care and reducing theoverall cost incurred by the employer, and more particularly to a methodfor application by a healthcare quality management firm (HQM) ofcharacterizing the healthcare situation of an employer who pays forhealthcare, comparing that healthcare situation to that of a geographicarea in which the employer resides, identifying factors affecting thequality and cost of the healthcare, and recommending action foraddressing the factors by applying resources at levels corresponding tothe relative affect of the factors on the quality and cost of thehealthcare.

BACKGROUND OF THE INVENTION

Employer sponsored healthcare benefits are of tremendous value toemployees and their families. Such benefits, on the other hand,typically constitute a significant portion of an employer's totaloperating costs. Unfortunately, as medical costs continue to increase,the cost of providing employer sponsored healthcare benefits willcontinue to increase.

Currently, many employers attempt to offset the rising costs ofproviding healthcare benefits by shifting the cost to employees. Ofcourse, only so much of the expense can be shifted to employees. At somepoint, the cost incurred by the employees will become prohibitive, andemployer sponsored healthcare will no longer be seen as a benefit. Someemployers attempt to monitor the price of certain healthcare services,but without information relating to the quality of the services, costinformation is of limited value. Other employers have attempted toreduce their healthcare expenses by sponsoring health fairs or wellnessscreenings. This approach, while somewhat effective in promptingpreventative healthcare, is not a focused expenditure of resources. Forthe majority of employees who are healthy, the money spent on wellnessscreenings is essentially wasted. Finally, employers sometimes attemptto negotiate the fixed costs associated with administering healthcarebenefits. Again, since these costs typically make up only a smallportion of the total cost, even successful negotiation attempts willhave a limited impact on the employer's bottom line.

In short, employers have been largely unsuccessful in their attempts tocontrol healthcare costs while ensuring a high level of care. Employerssimply lack the information necessary to identify the most significantfactors affecting their healthcare costs, to quantify and compare theperformance of healthcare providers, and to apply their resources in away that most effectively reduces both the overall consumption ofhealthcare and the costs of the services consumed while maintaining orimproving the quality of the healthcare benefits they provide.

SUMMARY OF THE INVENTION

The present invention provides a method of optimizing healthcareservices consumption through analysis of the demographic and wellnesscharacteristics of an employee population (including employees andemployee family members, hereinafter, “patients”), analysis of thequality and cost efficiency of the practices of providers used by thepatients, and intervention with patients and providers to improve theoverall health of the patients, the practices of the providers, and thecost efficiency of the employer provided healthcare plan. The method, inone embodiment thereof, includes the steps of assessing the healthcaresituation of the employer as it relates to normative characteristics ofa health economic zone including the patients, identifying patients fromthe covered population likely to generate expensive healthcare claimsrelative to the other patients based on data representing pasthealthcare claims generated by the patients, periodically determiningwhether these patients have obtained healthcare services that satisfypredetermined requirements, identifying qualified providers in thehealth economic zone who provide high quality, cost efficient healthcareservices relative to other providers in the health economic zone basedon data representing past practice patterns of the providers, promptingpatients who have not obtained healthcare services that satisfy thepredetermined requirements to obtain additional healthcare services fromthe qualified providers, and responding to healthcare requests frompatients by determining whether the requesting patient is seeking toobtain healthcare services from a qualified provider, and, if not,urging the patient to obtain services from a qualified provider.

The features and advantages of the present invention described above, aswell as additional features and advantages, will be readily apparent tothose skilled in the art upon reference to the following description andthe accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a conceptual diagram of participants in a healthcareconsumption situation that may be optimized using a method according tothe present invention.

FIG. 2 is a conceptual diagram of an interrelationship between a centraldatabase and the participants shown in FIG. 1.

FIG. 3 is a flow diagram depicting steps included in one embodiment ofthe present invention.

FIG. 4 is a conceptual diagram of a health economic zone.

FIGS. 5-15 are illustrations of reports generated according to anembodiment of the present invention.

FIG. 16 is a flow diagram of a process for evaluating the practicecharacteristics of healthcare providers.

FIG. 17 is a flow diagram depicting steps included in one embodiment ofthe present invention.

DETAILED DESCRIPTION OF EMBODIMENTS OF THE INVENTION

The embodiments described below are merely exemplary and are notintended to limit the invention to the precise forms disclosed. Instead,the embodiments were selected for description to enable one of ordinaryskill in the art to practice the invention.

FIG. 1 depicts a relationship among participants in a typical employerprovided healthcare situation. In this example, the employer 10 isself-insured and provides funds, based on predicted healthcare costs, toa third party administrator (TPA 12) of healthcare benefits for payingemployee healthcare claims. Of course, also involved in thisrelationship are the healthcare consumer, patient 14, the healthcareprovider 16 (e.g., a physician or a facility such as a hospital,laboratory, etc.), a pharmacy 18, a pharmacy benefit manager (PBM 19), aPPO 20, and a healthcare quality management firm (HQM 13). As shouldbecome apparent from the following description, HQM 13 could perform thefunctions of TPA 12. Thus, except where expressly indicated otherwise ormandated by the context of this description, references to HQM 13 mayinclude HQM 13 and TPA 12.

In a typical transaction associated with a healthcare claim, patient 14visits provider 16 to obtain healthcare services and/or products such asdrugs. For simplicity, this description collectively refers to servicesand products as healthcare services. Provider 16 submits a claim to PPO20 (or alternatively directly to TPA 12) in an amount corresponding tothe cost of the services. Provider 16 may also write a prescription thatis received by a pharmacy 18. In that event, pharmacy 18 submits a claimto PBM 19, which in turn submits a claim to TPA 12. As is well known inthe art, PPO 20 (or alternatively TPA 12) typically discounts orreprices the claimed charges based on an agreement between provider 16,pharmacy 18, and PPO 20. The repriced claim is submitted to TPA 12 forpayment. TPA 12 accesses funds in the healthcare account of employer 10to pay provider 16 and PBM 19 the repriced claim amounts. PBM 19 thenforwards a payment to pharmacy 18. TPA 12 then also informs patient 14of the patient's payment responsibility that arises as a part of theapplication of the terms of the underlying benefit plan when it does notpay 100% of eligible charges. Patient 14 then sends a payment toprovider 16. The above-described example assumes that TPA 12 is separatefrom HQM 13. If HQM 13 functions as a combination of HQM 13 and TPA 12,then HQM 13 interacts directly with employer 10, patient 14, provider16, PBM 19, and PPO 20 in the manner described with reference to TPA 12above.

As should be apparent from the foregoing, throughout each suchtransaction, TPA 12 has access to all of the material claim information.TPA 12 shares this information with HQM 13, which may contact employer10, patient 14, and/or provider 16. Accordingly, as will be described indetail below, HQM 13 is in a position to facilitate change in and/ordirectly influence the healthcare situation to control the cost incurredby employer 10 and to encourage consumption of healthcare from highquality providers 16. Thus, HQM 13 is described below as practicing thepresent invention as a service for the benefit of its clients, employers10, and patients 14 including the clients' employees and their familymembers.

According to one embodiment of the present invention, TPA 12 maintains adatabase 22 including a variety of different types of information fromemployer 10, provider 16, PBM 19, and PPO 20 as depicted in FIG. 2. Asis further described below, TPA 12 also updates information included indatabase 22 as a result of its interaction with HQM 13. Database 22 maybe maintained on any of a variety of suitable computer-readable mediasuch as a hard drive of a computer. While FIG. 2 suggests contributionsof information to database 22 by each of employer 10, TPA 12, provider16, PBM 19, and PPO 20, it should be understood that such informationmay not be provided directly to database 22. Instead, TPA 12 may receiveinformation from the other participants and enter and/or otherwiseprocess the information for storage in database 22. For example,information may be transferred electronically from employer 10, provider16, PBM 19, PPO 20, and HQM 13 to TPA 12 via a network or multiplenetworks. Moreover, TPA 12 may physically reside at multiple locations,each of which receives information from the other participants. Suchmultiple locations may be connected together via a network configured topermit simultaneous access to database 22 through a server. Any suitablemethod of transferring information and storing such information ineither a centralized or distributed database 22 is within the scope ofthe invention. For simplicity, the transfer of information is describedherein as occurring electronically over a network, and database 22 isdescribed as a centralized database accessible by a single TPA 12location.

As is further described below, the information stored in database 22permits HQM 13 to evaluate the healthcare situation of employer 10,including the cost information, the healthcare characteristics ofpatients 14, and the performance of providers 16 used by patients 14covered under the healthcare plan provided by employer 10. Accordingly,the information in database 22 includes employer information, patientinformation, provider information, pharmacy information, and claimsinformation that may relate to some or all of the other types ofinformation. The employer information includes information identifyingemployer 10, patients 14 covered under the employer provided healthcareplan, PPO 20 associated with employer 10, as well as historical datathat characterizes changes in the healthcare situation of employer 10over time. The patient information includes the name, address, socialsecurity number, age, and sex of each patient 14 covered under thehealthcare plan provided by employer 10. The provider informationincludes the name, tax identification number, address, and specialty ofa plurality of healthcare providers across a large geographic region,such as the entire United States. As is further described below,portions of the provider 10 information are associated with employer 10.These portions correspond to the providers 16 that provide services topatients 14. The pharmacy data includes information identifying thetype, quantity, and dosage of drugs associated with a particularprescription for a particular patient 14 as well as the social securitynumber of the patient 14. This information permits association ofprescription drug claims with patients 14. These claims can be furtherassociated with the provider 16 that wrote the prescription by accessingthe claims data (described below) associated with the patient 14 whofilled the prescription to determine which provider 16 patient 14 sawprior to obtaining the prescription. Alternatively, an identifier may beincluded in the pharmacy data with each prescription entry thatidentifies provider 16.

The claims data stored in database 22 include portions of theabove-described data, but may be organized or associated with aparticular claim. More specifically, a claim may include informationidentifying and/or describing employer 10, patient 14, provider 16,pharmacy 18, PBM 19, and PPO 20. The claim may further includeinformation describing the condition or symptoms of patient 14 thatgenerated the claim, the diagnosis of provider 16, the proceduresordered by provider 16 to treat the diagnosed condition as identified bycommonly used procedure codes, and the costs (both original charges andrepriced amounts) of the healthcare services associated with the claim.

As indicated above, the information stored in database 22 comes from avariety of sources. For example, when an employer 10 becomes a newclient of HQM 13, PPO 20 servicing employer 10 may provide HQM 13 withenrollment data including employer information, employee information,and associated past claims information. HQM 13 may then process thatinformation for addition to database 22. Periodically, PPOs 20 ofemployers 10 transfer claims information to TPA 12 (i.e., as the claimsinformation is processed by PPOs 20). As indicated above, in addition toinformation relating to associated healthcare services, this claimsinformation may include employee information, provider information, andpharmacy information. Additionally, PBMs 19 (or data transfer servicesworking with PBMs 19) periodically transfer pharmacy information to TPA12. As further described below, each time new information is provided toTPA 12, TPA 12 and/or HQM 13 may process the information such that it isassociated with a particular employer 10, a particular patient 14, or aparticular provider 16.

Referring now to FIGS. 3 and 4, one embodiment of the method accordingto the present invention may be generally described as involving threebasic steps: analyzing the healthcare situation of employer 10,improving the healthcare consumption characteristizcs of patients 14,and improving the overall performance characteristics of providers 16used by patients 14. One process for analyzing a healthcare situation ofan employer 10 is depicted in FIG. 3. In general, after all of therelevant information regarding employer 10, patients 14 associated withemployer 10, and providers 16 used by patients 14 resides in database22, HQM 13 executes software (as further described below) to accessdatabase 22 and identify a Healthcare Economic Zone (HEZ 24, FIG. 4)corresponding to employer 10 (step 26). As shown in FIG. 4, HEZ 24corresponds to a geographic area that includes all patients 14associated with all employers 10 and providers 16 used by patients 14(including physicians 28 and facilities 30, such as hospitals). HEZ 24may be defined to correspond to Hospital Service Areas set forth by theDartmouth Atlas project, a funded research effort of the faculty of theCenter for the Evaluative Clinical Sciences at Dartmouth Medical School.Essentially, HEZs are based on the zip codes of the residentialaddresses of patients 14 stored in database 22 and the locations ofproviders 16 servicing those zip codes. In other words, an HEZ 24includes a geographic region in which patients 14 tend to obtain theirprimary healthcare. For example, assuming patients 14 associated withemployer 10 all reside in three adjacent zip codes that are serviced byone facility 30 (also within one of the three zip codes), then thosethree zip codes are included in HEZ 24. However, if facility 30 alsorefers patients 14 to, for example, specialist providers 16 in a fourthzip code, then the fourth zip code is also included in HEZ 24. FIG. 4shows HEZ 24 fully contained within a larger geographic area such as astate 32. It should be understood, however, that HEZs 24 (or theequivalent of HEZs 24) may extend across state lines.

Referring again to FIG. 3, step 34 indicates that information indatabase 22 corresponding to employer 10 (i.e., employer information,patient information, claims information corresponding to patients 14associated with employer 10, and provider information) is analyzed toevaluate the healthcare situation of employer 10. In step 36, theemployer specific data is compared to generalized data relating to HEZ24 as is further described below. As indicated in FIG. 3, the results ofthe analyses performed in steps 26, 34, and 36 may be processed in theform of provider reports 38, employer reports 40, and patient reports42, some or all of which may be provided to employer 10 as shown in FIG.1 as part of the process of analyzing the healthcare situation ofemployer 10. Step 44 depicts the process of updating database 22 as HQM13 and/or TPA 12 receive claims information and/or changes in thepopulation of patients 14 associated with employer 10 as a result ofemployees being hired by or departing from employer 10, or changes inthe family situation of the employees. As should be apparent from thefigure, the process of analyzing the healthcare situation of employer 10is therefore continuously updated and may result in generation ofperiodic reports for employer 10 and HQM 13 to track changes in thehealthcare situation over time.

FIG. 5 depicts an example of an employer report 40. Although chart 46 ofFIG. 5 does not compare employer 10 information to HEZ 24 information,it is an employer report 40 because it provides employer 10 informationregarding the costs of healthcare services in the HEZ 24 in whichemployer 10 (more accurately, patients 14 associated with employer 10)resides. Chart 46 includes a specialty column 48, a total allowedcharges column 50, a total allowed charges at normative costs column 52,a percent of excess charges column 54, and an excess charge per life peryear column 56. Chart 46 provides employer 10 information regarding therelative costs of healthcare services (by specialty) in the employer'sHEZ 24 as compared to the costs in a larger geographic area thatincludes HEZ 24 (e.g., state 32, the Midwest, the southeast, etc.). Inthis example, providers 16 in HEZ 24 charged $4,251,526 (column 50) forcardiology services over the course of a predetermined time period, suchas two years. Column 52 shows that the normative costs for such servicesis $4,488,559 for the same number of healthcare consumers (i.e.,patients 14) over the same predetermined time period. More specifically,the dollar amounts in column 52 are derived by first adding all of thecharges for cardiology services in the larger geographic area for thepredetermined time period and dividing the total by the number ofhealthcare consumers in the larger geographic area. Then, this “averagecardiology charge per healthcare consumer” is multiplied by the numberof healthcare consumers in HEZ 24. As shown in column 54, HEZ 24experienced cardiology costs that were 5.3 percent below the normativecardiology charges. Finally, column 56 simply converts the percentagedeviation from the normative charge into a dollar value divided by thenumber of healthcare consumers in HEZ 24 and the number of years in thepredetermined time period.

Line 58 shows the totals for all specialties or Major PracticeCategories (MPCs). Lines 60 and 62 illustrate a situation wherein HEZ 24is serviced by more than one PPO 20. Since all of the claims informationin database 22 is associated with a particular PPO 20, the chargesassociated with all claims of healthcare consumers in HEZ 24corresponding to PPO network A and PPO network B may be separated basedon the PPO that handled the claim. Thus, lines 60 and 62 depict therelative usage of the PPOs by healthcare consumers in HEZ 24 (column50), the normative usage values for each PPO in a larger geographic area(eg., state 32) (column 52), the cost performance of the PPOs for HEZ 24relative to the cost performance of the PPOs across state 32 (column54), and the meaning of that relative performance on a dollars perpatient 14 per year basis (column 56). Lines 64 and 66 provide similarinformation for two hospitals used by healthcare consumers in HEZ 24.

As should be apparent from the foregoing, employer 10 may readily scandown total allowed charges column 50 to determine the specialties mostlikely to contribute significantly to the employer's overall healthcarecosts. Columns 54 and 56 permit employer 10 to readily identify thosepractice categories having charges that deviate most from the average ornormative charges. In this manner, employer 10 (and HOM 13) can isolatethe practice categories that have the most potential for providing themost significant reduction in the overall healthcare costs of employer10.

Another employer report 40 (chart 68 of FIG. 6) follows the same formatas chart 46, but compares the actual healthcare costs of employer 10 tothe typical costs in HEZ 24. Chart 68 includes a specialty column 70, atotal costs column 72, a normalized costs in HEZ 24 column 74, a percentexcess column 76, and an excess cost per life per year column 78. Column72 represents the total costs employer 10 incurred for the variousspecialties listed in column 70 during a predetermined time period. Thenormalized amounts in column 74 represent the expected cost in HEZ 24for an employer having the same number of patients 14 as are associatedwith employer 10. For example, assuming a total cost for cardiology inHEZ 24 of $17,122,789 for 35,623 healthcare consumers in HEZ 24, theaverage cardiology cost per healthcare consumer is $480.67. Assumingthat employer 10 has 150 patients 14, then the expected total cost forcardiology services (i.e., the normalized costs in HEZ 24, column 74) is$72,100. Accordingly, employer 10 has incurred costs for cardiologyservices that are 23.7% below the anticipated amount for an employer thesize of employer 10 located in HEZ 24 as shown by column 76. Column 78reflects this percentage in a per patient 14 per year dollar value.

As should be apparent from the foregoing, chart 68 could readily berevised to reflect similar information for actual consumers of theparticular specialties as opposed to patients 14 and healthcareconsumers generally. In other words, if only nine patients 14 usedcardiology services over the predetermined time period (resulting in atotal cost of $55,000), column 74 could be modified to reflect theexpected amount for nine of the average consumers of cardiology servicesin HEZ 24 over the predetermined time period. Of course, columns 76 and78 would then reflect the difference between these values on apercentage and per life per year basis, respectively.

FIG. 7 is another employer report 40 that summarizes the illness burdenand demographics of HEZ 24 associated with employer 10. Chart 80includes a description column 82, an HEZ 24 data column 84, a normativevalue a larger geographic area including column 86 for HEZ 24, a percentexcess column 88, and an excess per life per year column 90. It is wellknown that healthcare consumption is greater for adults verses children(other than newborn children), for females verses males, and for olderadults verses younger adults. Obviously, healthcare consumption is alsogreater for individuals having certain types of pre-existing illnessesas compared to healthy individuals. The method of the present inventionuses these factors to compute a healthcare index (line 92 in FIG. 7) forHEZ 24 in which patients 14 associated with employer 10 reside. Themethod of the present invention calculates the healthcare index for anHEZ 24 using Episode Risk Group (ERG) scores inherent in the health riskassessment process provided by Symmetry Health Data Systems, Inc. anddescribed in “A New Approach to Health Risk Assessment,” a white paperavailable from Symmetry Health Data Systems, Inc., the disclosure ofwhich is hereby incorporated herein by reference. A healthcare index foreach patient 14 in HEZ 24 is computed using a retrospective analysis,and the index for HEZ 24 is derived by calculating an average index forall patients 14 in HEZ 24. As shown in column 84 of FIG. 7, HEZ 24 has9,808 patients 14 having an average age of 42, and comprising 74.8%adults, 38.6% of whom are female. These factors result in a healthcareindex for HEZ 24 of 1.506. As shown in column 88, this healthcare indexis 50.6% above the normative healthcare index of 1.0 for the largergeographic area. This high healthcare index results from a higher thantypical percentage of females and adults in HEZ 24 and a higher thantypical percentage of individuals with health risk factors. Morespecifically, as shown in column 88 of FIG. 7, 10.8% of the overage isdue to atypical demographics (i.e., an older and more heavily femalepopulation). 39.8% of the overage is due to the atypical illness burdenof the population (i.e., a population with health conditionscorresponding to higher than typical health risk factors). Accordingly,an employer 10 in HEZ 24 should expect to have healthcare costs that aregreater than the typical costs of the larger geographic region. Itshould be understood that a similar report could readily be generatedcomparing the illness burden and demographic information of a particularemployer 10 to information describing the HEZ 24 in which patients 14associated with employer 10 reside.

Referring now to FIG. 8, a patient report 42 is shown summarizing thechronic illnesses of patients 14 associated with employer 10. It is wellknown that typically 80% of an employer's healthcare costs are generatedby approximately 20% of the covered population of patients 14. That 20%of the population generally has a high incidence of chronic illness.Accordingly, chart 94 of FIG. 8 is generated to provide employer 10 asummary of its chronically ill patients 14.

As shown, column 96 lists various chronic illnesses. While the method ofthe present invention may track any number of chronic illnesses, onlysix are shown in FIG. 8. Column 98 shows the number of patients 14having each of the listed illnesses. Column 100 shows the number ofthose patients 14 listed in column 98 that have at least one year ofclaims history (i.e., have submitted claims that were added to database22). Column 102 shows the number of patients 14 that have satisfied theminimum annual care requirements (MACRs) recommended for treating thechronic illness or illnesses from which they suffer. Column 104 simplyexpresses the number in column 102 in the form of a percentage of thetotal patients 14 suffering from the listed illness. The MACRs for eachchronic illness of chart 94 are listed in column 106 and obtained usingsoftware available from McKesson Corp., a supplier of information andmanaged care products and services for the health care industry. Inparticular, McKesson's CareEnhance Resource Management Software (CRMS)provides such information. As the method of optimizing healthcareservices consumption described below is practiced, periodic reports suchas chart 94 of FIG. 8 will show improvements in the number of patients14 that satisfy the MACRs associated with their particular illness(es).

Chart 110 of FIG. 9 shows the chronic illness status of patients 14associated with employer 10 in terms of co-morbidities. Chart 110includes a description column 112, a current patient column 114, apercent of current covered patients column 116, a previous patientcolumn 118, a percent of previous covered patients column 120, and apercent of database driven norms column 122. As shown in column 114, ofthe 993 total patients 14 covered under a healthcare plan provided byemployer 10, a total of 619 have a single chronic illness, 236 have twochronic illnesses, 86 have three chronic illnesses, etc. Column 116expresses the number of patients 14 listed in column 114 in terms of thepercentage of the total patient 14 population. Columns 118 and 120include similar information representing the status of the chronicallyill at a previous date. Employer 10 can monitor changes in the chronicillness status of its patients 14 by comparing these two sets ofcolumns. Finally, column 122 shows the typical percentage of individuals(based on all individuals reflected in the database) with the particularnumber of chronic illnesses.

In addition to summarizing patients 14 having chronic illnesses, themethod of the present invention also includes the step of performing arisk stratification of all patients 14 covered by employer 10. Theresults of this risk stratification step are provided to employer 10 asan patient report 40. Chart 124 of FIG. 10 is an example of such anpatient report 42. As shown, chart 124 includes a family identificationnumber column 126, a patient identification column 128, an age column130, a gender column 132, a healthcare index column 134, and a predictedcost column 136. The primary purpose of chart 124 is to display patients14 in order of their associated healthcare index listed in column 134.The healthcare index is derived using the McKesson CRMS software asdescribed above, which takes into account the age, gender, chronicillnesses, and co-morbidities of each patient 14. Also, by analyzingclaims data describing prescriptions, the CRMS software imputesillnesses of patients 14 based on the number and types of medicationsprescribed for patients 14. Thus, the healthcare index is used to rankpatients 14 in terms of their likelihood of generating large medicalexpenses in the near future. It should be noted that not only thechronically ill are identified by the healthcare index. Other patients14 having conditions that are not considered chronic may have highhealthcare indices. Column 136 provides a predicted cost associated witheach patient 14 based on their healthcare index. More specifically,column 136 is derived by calculating the total expense associated withthe normative population, and dividing that amount by the total numberof ERG risk points of the normative population to get dollars per riskpoint (prospectively). Then, using the method of the present invention(and not the CRMS software), the healthcare index of column 134 ismultiplied by the dollars per risk point value.

The above-described employer reports 40 and patient reports 42 areillustrative of the way in which the method of the present inventiondetermines which patients 14 covered by employer 10 should receiveintervention or proactive coaching (as further described below anddepicted in FIG. 1), and at what level of intensity. In other words,since chronically ill patients 14 generally generate large healthcarecosts, chronically ill patients 14 should be monitored and coached mostactively and at levels corresponding to the number of chronic illnessesfrom which they suffer. Likewise, patients 14 having high healthcareindices because of their age, gender, illnesses, etc. should bemonitored and coached most actively and at levels corresponding to theirhealthcare index. Using the above-described approach, patients 14 thatrequire proactive coaching typically constitute approximately 25% of thetotal patient 14 population. It has been shown that this 25% portion ofthe patient 14 population typically generates 90% of the totalhealthcare costs incurred by employers 10.

As indicated above, the method of the present invention also generatesphysician reports 38 such as chart 138 shown in FIG. 11. Chart 138 is anexample of a comparison of various characteristics of the practice of aparticular provider 16 to the practices of other providers 16 in thesame specialty. In order to make such comparisons, the claimsinformation in database 22 may be analyzed on the basis of “episodes” ofhealthcare. This analysis is performed using software applicationsavailable from McKesson Corp., which analyze the services and costsassociated with claims originated by a particular provider 16. Anepisode is defined as a healthcare consumption sequence including allhealthcare services consumed by a patient 14 for a particular healthcareproblem. Episodes may include healthcare services ordered by a physicianas a result of an initial office visit (e.g., tests, X-rays, etc.),healthcare services associated with a subsequent hospital visit (e.g.,for surgery), and healthcare services associated with aftercare orfollow-up visits to the physician.

The analysis of claims information grouped by specialty episodes permitsidentification of providers 16 having practice patterns that result inlow total costs for the types of healthcare problems they treat ascompared to other providers 16 in the specialty. Additionally, providers16 who deliver high levels of post-primary preventative care servicesfor chronically ill patients 14 can be identified. Finally, specificundesirable characteristics of a provider's 16 practice patterns can beidentified such as up-coding, ordering inappropriate services, vague orinvalid diagnostic codes, and services that are performed toofrequently. All of this information is available from the 10 claimsinformation stored in database 22.

Referring back to FIG. 11, Bar 140 of chart 138 represents thepercentage of procedures ordered by a particular provider 16 (physicianID #223776) that were determined to be inappropriate for the diagnosisreflected in the claims information associated with the evaluatedepisodes. Bar 142 represents similar data for the entire specialty.Comparing bar 140 to bar 142 shows that this particular anesthesiologistordered inappropriate procedures at nearly double the rate of others inthe specialty. The remaining bar groups 144, 146, 148, 150, and 152permit similar comparisons for the practice pattern characteristicsindicated on chart 138.

As further described below, one of the steps of a method according tothe present invention involves determining whether providers 16 used byemployees 14 of employer 10 provide healthcare in a manner thatsatisfies certain criteria. If so, these providers 16 are identified asQuality Service Providers or QSPs. To achieve a QSP designation orrating, providers 16 must, based on claims information stored indatabase 22, pass three screens or quantitative tests of the providers'16 performance or practice characteristics. Any provider 16 who failsone or more of these tests is identified for purposes of practicing thepresent invention as a non-certified QSP (“NCQSP”).

The first test (“the CEI test”) is primarily economic. Using claimsinformation in database 22, the software of the present inventiongenerates a Cost Efficiency Index (CEI) for each provider 16. The CEIrepresents the actual total cost of care provided and/or ordered byprovider 16 for completed episodes, divided by the total average cost ofsuch care for similar episodes treated by other providers 16 in thespecialty. In other words, the cost to employer 10 for the healthcaredelivered and/or ordered by provider 16 for all completed episodes forall patients 14 is first extracted from the claims information indatabase 22. Then, the total cost for all similar episodes handled byall providers 16 tracked in database 22 is determined, and divided bythe total number of episodes to arrive at an average cost per episode inthe specialty. Finally, the average cost per episode for provider 16 isdivided by the average cost per episode in the specialty to arrive atthe CEI for provider 16. If provider 16 has a CEI that exceeds apredetermined threshold (e.g.,) 125% or more above that of others in thespecialty of provider 16) and is statistically higher that the averagefor the specialty (i.e., sufficient claims information is contained indatabase 22 to calculate the CEI of provider 16 with a statisticallyacceptable confidence level such as at the p 0.1 level), then provider16 failed the CEI test and will be designated a NCQSP. A sample reportof the data used to complete a CEI analysis is shown in FIG. 12.

The second test in the QSP rating process (“the service rate test”)evaluates the preventative care practices of providers 16. As is wellknown in the field of medical care, preventative care services maysignificantly affect the overall cost of healthcare, particularly thoseservices provided to treat chronic illnesses to prevent those illnessesfrom progressing or resulting in other health complications. TheMcKesson software permits extraction of data representing the number andtypes of preventative care services ordered by providers 16 fortreatment of chronic conditions. In one embodiment of the invention,nineteen chronic conditions are tracked. To evaluate a particularprovider 16, the data representing the preventative care services forprovider 16 is extracted and compared (according to the method of thepresent invention) to a minimum number and particular types of servicesconsidered acceptable in treatment of the particular chronic conditionstreated by provider 16. This analysis results in a service rate forprovider 16. More specifically, the total number of services ordered forchronically ill patients treated by provider 16 is determined, and thendivided by the number of services required for such patients to achievecompliance with the associated MACRs. This service rate, or fraction ofrecommended MACRs, is then compared to the typical service rate in theappropriate specialty. If provider 16 has a service rate that is bothless than a certain percentage of the typical service rate (e.g., hasordered 75% or less of the services required to achieve compliance withthe associated MACRs) and statistically significantly lower than theaverage for the specialty (i.e., a statistically significant sample sizeis available in database 22 to obtain confidence at the p 0.1 level),then provider 16 failed the service rate test and is designated a NCQSP.A sample report representing the results of a service rate analysis isshown in FIG. 13.

The third test (the “practice patterns test”) involves an evaluation ofthe overall practice patterns of providers 16. More specifically, theMcKesson clinical software is used to extract the number of occurrencesof up-coding, ordering inappropriate services, vague or invaliddiagnostic codes, and services that are performed too frequently, bothfor the particular provider 16 being evaluated, and for the specialty asa whole. Each practice pattern category is evaluated according to themethod of the present invention to determine whether provider 16practices in a manner that results in a practice patterns challenge ratethat exceeds a predetermined multiple of the typical practice patternpercentages (e.g., 200% or more than the typical practice patterns) andis statistically significantly higher than the average percentages(e.g., at the p 0.01 level). If so, provider 16 failed the practicepatterns test and is designated a NCQSP. A sample report representingthe results of a practice patterns analysis is shown in FIG. 14.

According to the present invention, providers 16 that pass each of thethree tests are assigned a QSP designation, indicating that providers 16practice high quality medicine in a cost effective manner. As will befurther described below, these QSP providers 16 are targeted by thepresent method for providing a maximum percentage of the overallhealthcare consumed by patients 14 of employer 10. In addition to thebasic QSP/NCQSP distinction resulting from the above-described process,providers 16 may be further ranked based on the results of theabove-described tests. For example, the QSP category of providers 16 maybe divided into “A” level QSP providers 16 and “B” level QSP providers16. “A” level QSP providers 16 may be defined as providers 16 who havehistorical claims data in database 22 representing at least fiveepisodes of the relevant type (“sufficient episodic data”), pass the CEItest with a CEI of less than 100% of the typical CEI in the specialty,and pass both the service rate test and the practice patterns test. “B”level QSP providers 16 may include providers 16 who (1) do not havesufficient episodic data, or (2) have sufficient episodic data and passall three tests, but with a CEI of greater than or equal to 100% of thetypical CEI in the specialty.

Similarly, providers 16 falling into the NCQSP category may be furtherranked relative to one another to provide an ordered listing of NCQSPs.For example, “C” level NCQSP providers 16 may be defined as providers 16who have sufficient episodic data, pass the CEI test, but fail one ofthe service rate or practice patterns tests (not both). “D” level NCQSPproviders 16 may be defined as providers 16 who have sufficient episodicdata and (1) fail the CEI test with a CEI of less than 150% of thetypical CEI in the specialty or (2) fail both the service rate andpractice patterns tests. Finally, an “E” level NCQSP provider 16 may bedefined as a provider 16 with sufficient episodic data who fails the CEItest with a CEI that is at least 150% greater than the typical CEI inthe specialty. Thus, providers 16 may be categorized in levels “A”through “E.” This ranking permits targeting not only QSPs, but “A” leveland “B” level QSPs, or NCQSPs that at least have the best relativerankings on the list of NCQSPs.

Another example provider report 38 is shown in FIG. 15. Chart 154 ofFIG. 15 is a listing of NCQSPs in descending order. The group of columnscollectively assigned reference designation 156 identifies the providers16 by ID, name, and location. Column 158 lists the number of episodes indatabase 22 associated with each provider 16. Column 160 lists theabove-described CEI for each listed provider 16. The greater the CEIlisted in column 160, the more significant the provider's deviation fromthe practice patterns of other providers 16 in the specialty.Consequently, those providers 16 listed near the top of chart 154 willprovide healthcare resulting in a greater cost to employer 10. In oneembodiment of the invention, listings of NCQSPs such as chart 154 aredivided into thirds for purposes of practicing the invention as furtherdescribed below.

Referring now to FIG. 16, a flow diagram of the above-described processfor assigning QSP or NCQSP designations to providers 16 is shown. Atstep 162, claims information corresponding to a particular provider 16is extracted from database 22 to determine whether provider 16 hassufficient episodic data (e.g., at least five episodes of the relevanttype). If not, then provider 16 is designated an unknown, “B” level QSP.If provider 16 has sufficient episodic data stored in database 22, theneach of the three above-described tests are performed as indicated atstep 163. At step 164, the results of the CEI test are analyzed. If theCEI is 125% or more greater than the typical CEI in the specialty andsatisfies the above-described statistical significance criteria, thenprovider 16 is marked as failing the CEI test (step 165). Otherwise,provider 16 is marked as passing the CEI test (step 166). Similarly, theresults of the practice patterns test are analyzed at step 167. Ifprovider 16 has a service challenge rate of 200% or more than thetypical rate in the specialty and satisfies the above-describedstatistical significance criteria, then provider 16 is marked as failingthe practice patterns test (step 168). Otherwise, provider 16 is markedas passing the practice patterns test (step 169). Finally, the resultsof the service rate test are analyzed in a similar manner at step 170,and provider 16 is marked as failing (step 171) or passing (step 172)the service rate test as a result of the analysis.

As shown at step 173, “A” level QSPs are identified as providers 16 whoare marked as passing all three tests and achieved a CEI of less than 1.If a provider 16 is marked as passing all three tests, but has a CEIthat is greater than or equal to 1, then provider 16 is designated a “B”level QSP as indicated by step 174. The remaining providers 16 are NCQSPproviders 16. At step 175, the method of the present inventionidentifies “C” level NCQSPs at step 176 as providers 16 who are markedas passing the CEI test, but failing one of the other two tests (but notboth). At step 177, the lowest level providers 16 (“E” level NCQSPs) areidentified as providers 16 who are marked as failing the CEI test with aCEI of at least 1.5. Any remaining providers 16 are designated “D” levelNCQSPs as indicated at step 161. “D” level NCQSPs include providers 16who are marked as failing the CEI test, but with a CEI of less than 1.5,and providers 16 who are marked as failing both the service rate andpractice patterns tests. This process of evaluating providers 16 forpurposes of determining QSP/NCQSP status and levels within each categoryis repeated periodically to maintain an updated listing in database 22.It should be further understood that the particular numeric thresholdvalues used in each of the three tests may readily be changed to affectthe number of providers 16 falling into each of the five levels withoutdeparting from the principles of the invention. The designations forproviders 16 resulting from the above-described process are used toimprove the quality and cost-efficiency of the healthcare servicesconsumed by employees 14 of employer 10 in the manner described below.

Referring now to FIG. 17, a flow diagram representing a portion of amethod for optimizing healthcare services consumption is provided. Atstep 178, the claims information corresponding to patients 14 isextracted from database 22. Step 178 results in the data necessary toidentify patients 14 having chronic illnesses (step 180) and to rankpatients 14 according to the above-described risk stratification process(step 182). As indicated above and shown in FIG. 1, the method of thepresent invention, in one form thereof, involves intervention withpatients 14 by registered nurses and other staff of HQM 13. Thisintervention or proactive coaching follows one or both of the two pathsdepicted in FIG. 17. First, for patients 14 identified as having one ormore chronic illness, the method of the invention determines at step184, based on claims information associated with such patients 14,whether the MACRs associated with the illness(es) have been satisfied.If the MACRs for a particular patient 14 have not been satisfied, then arepresentative of HQM 13 (e.g., a registered nurse or other staffmember) contacts patient 14 to remind patient 14 of the need to schedulethe healthcare necessary to satisfy the MACRs. This contact may beaccomplished by any mode of communication including by phone, email,fax, mail, or any combination thereof. Preferably, the representative ofHQM 13 has a live conversation with patient 14 to impress upon patient14 the importance of satisfying the MACRs associated with the patient'schronic illness.

At step 188, the representative of HQM 13 may also contact provider 16of healthcare services associated with the chronic illness(es) ofpatient 14. As a result of this contact, the representative enlists thecooperation of provider 16 in the effort to persuade patient 14 tosatisfy the MACRs. As should be apparent from the foregoing, a goal ofthis intervention is to improve the health of patient 14 and minimizethe cost to employer 10 by avoiding the increased healthcare expensestypically accompanying untreated chronic illnesses.

Steps 186 and 188 may result in the generation of a healthcare request.Specifically, patient 14 may respond to contact by the representative ofHQM 13 by scheduling an evaluation by provider 16 or other action towardsatisfying the MACRs associated with the chronic illness(es) of employee14. Step 190 represents the possibility that a healthcare request isgenerated. If so, the healthcare request is processed as described belowwith reference to the second path depicted in FIG. 17. Otherwise, apredetermined time period is allowed to pass before repeating theprocess of checking the compliance of patient 14 with the MACRsassociated with the chronic illness(es) of patient 14 and contactingpatient 14 and provider 16. Step 192 indicates this delay period.

When healthcare requests are generated, either as a result of the firstpath of FIG. 17 described above, or simply during the ordinary course ofemployee healthcare consumption, HQM 13 receives the healthcare requestat step 194. The healthcare request is associated with a particularpatient 14 based on the risk stratification process represented by step182. By determining the risk ranking of the requesting patient 14, HQM13 can perform intervention actions (as described herein) in the orderof ranking of patients 14. In other words, since it is not possible tocontact every patient 14 submitting a healthcare request, the ranking ofpatients 14 permits HQM 13 to focus first on patients 14 having ahighest risk ranking, and then (time and resources permitting) patients14 have a smaller likelihood of generating high cost healthcare claims.The method of the present invention next accesses database 22 todetermine whether provider 16 associated with the healthcare request iscurrently designated a QSP according to the process described above. Ifpatient 14 is requesting to obtain healthcare services from a QSP, thenthe healthcare request may be processed according to conventionalprocedures without intervention by representatives of HQM 13 asindicated by step 196. Alternatively, the QSPs resulting from theabove-described evaluation process may be ranked relative to one anotherand categorized into, for example, the “A” and “B” level QSPclassifications described above. In such an alternative embodiment, anadditional step (not shown) between step 196 and step 194 of contactingan patient 14 requesting healthcare from a “B” level QSP may beprovided. At that step, a representative of HQM 13 may attempt toinfluence patient 14 to obtain such services from a “A” level QSP.

If, on the other hand, the healthcare request seeks services from aNCQSP, then the ranking of the NCQSP (derived as explained above withreference to FIG. 16) is determined at step 198. At step 200, arepresentative of HQM 13 contacts patient 14 who generated thehealthcare request to urge patient 14 to obtain the requested servicesfrom a QSP. The representative may explain to patient 14 that variousother providers 16 within geographic proximity to patient 14 (determinedin the manner described below) have achieved the QSP designation forhigh quality, cost efficient healthcare, while provider 16 selected bypatient 14 has not achieved that designation. The representative mayfurther explain the implications of obtaining healthcare services fromNCQSPs, and attempt to assist patient 14 in rescheduling the requestedhealthcare services with a QSP. Additionally, if patient 14 refuses toswitch to a QSP, the representative may attempt to persuade patient 14to at least switch to a NCQSP that is ranked at a higher level than thecurrently selected NCQSP.

As described above, at step 200 of FIG. 14, the representative of HQM 13may list for patient 14 the variety of other providers 16 (specifically,QSPs) within a specific geographic proximity to patient 14. Such a listis generated by accessing database 22 using a software interfaceconfigured to permit the HQM 13 representative to input a desired radiusextending from the location of patient 14, thereby defining an area ofgeographic proximity surrounding patient 14. The software accessesdatabase 22, identifies the QSPs located within the selected geographicarea, and provides a listing to the HQM 13 representative. Using thissoftware and method, the representative may access listings of QSPswithin, for example, a five mile, ten mile, and/or fifteen mile radiusof patient 14.

In the event patient 14 refuses to obtain healthcare services from aprovider 16 other than the currently selected NCQSP, the method of thepresent invention determines (at step 202) the level of interventionrequired to minimize the costs of such services while maintaining highquality healthcare and the specific actions associated with thatintervention level. A plurality of actions may be taken by therepresentative of TPA 12, depending upon the level of interventionrequired. As described above, the NCQSP listings generated by thepresent invention may, for example, be divided into thirds (“C,” “D,”and “E” level NCQSPs). “E” level NCQSPs require the greatest level ofintervention because the healthcare provided by such NCQSPs, asevaluated by the three QSP tests described herein, most significantlydeviates from characteristics associated with desirable healthcareservices. “D” level NCQSPs require less intervention. Finally, providers16 designated “C” level NCQSPs require the least intervention. This“stepped-down” approach to intervention permits efficient usage of theresources available to HQM 13 in managing the healthcare expenses ofemployer 10.

As indicated above, providers 16 at the top third of a NCQSP listing(“E” level NCQSPs) receive the highest level of monitoring andindividual contact by representatives of HQM 13. If an “E” level NCQSPis identified at step 198 of FIG. 17, then step 202 obtains a listing ofintervention actions associated with “E” level NCQSPs. These actions mayinclude the following:

-   -   (1) Obtain criteria for any admission associated with the        healthcare request, including medical history, tests, and lab        work;    -   (2) Delay any admission for employee 14 until all days of        admission are approved by an appropriate representative of HQM        13;    -   (3) Complete a telephone evaluation with the NCQSP provider 16,        conducted by an appropriate HQM 13 representative, to evaluate        and discuss the need for any admission;    -   (4) Review the need to continue an admission after each day of        the admission;    -   (5) Delay any additional days of admission beyond the initial        length of stay until such additional days are approved by an        appropriate representative of HQM 13;    -   (6) Assign a representative of HQM 13 to provide assistance to        provider 16 in determining appropriate services to address the        healthcare problem and to report treatments proposed by provider        16 to an appropriate representative of HQM 13; and    -   (7) Contact provider 16 directly to discuss any questionable        proposed treatments as determined by an appropriate        representative of HQM 13.

If a “D” level NCQSP is identified at step 198 of FIG. 17, then step 202obtains a listing of intervention actions associated with “D” levelintervention. These actions may include the following:

-   -   (1) Obtain criteria for any admission associated with the        healthcare request, including medical history, tests, and lab        work;    -   (2) Assign a one-day length of stay and perform daily concurrent        review of additional days, requiring approval by an appropriate        representative of HQM 13 as needed;    -   (3) Require provider 16 to send notifications of admissions to        an appropriate representative of HQM 13;    -   (4) Complete a telephone consultation with provider 16,        conducted by an appropriate representative of HQM 13, if deemed        necessary by the representative of HQM 13; and    -   (5) Assign a representative of HQM 13 to provide assistance to        provider 16 in determining appropriate services to address the        healthcare problem and to report treatments proposed by provider        16 to an appropriate representative of HQM 13.

Finally, if a “C” level NCQSP is identified at step 198 of FIG. 17, thenstep 202 obtains a listing of intervention actions associated with a “C”level intervention. These actions may include the following:

-   -   (1) Obtain criteria for any admission associated with the        healthcare request, including medical history, tests, and lab        work;    -   (2) Assign a maximum two-day length of stay or less based on        conventional length of stay guidelines, and perform daily        concurrent review of additional days, requiring approval by an        appropriate representative of HQM 13 as needed; and    -   (3) Assign a representative of HQM 13 to provide assistance to        provider 16 in determining appropriate services to address the        healthcare problem and to report treatments proposed by provider        16 to an appropriate representative of HQM 13.

All of the various intervention actions listed above are represented bysteps 204 and 206 of FIG. 17. After all of the appropriate interventionactions have been completed, the healthcare request is fully processed.Additional healthcare requests may be received at step 194 andsimultaneously processed.

By applying the resources of HQM 13 to intervene with those patients 14presenting the greatest risk of generating high healthcare costs andproviders 16 most likely to provide the least desirable healthcare, themethod of the present invention may result in improvements to thehealthcare consumption habits of patients 14 and to the practicepatterns of providers 16, thereby resulting in an overall improvement ofhealthcare services consumed by patients 14 and cost efficiency realizedby employer 10.

The foregoing description of the invention is illustrative only, and isnot intended to limit the scope of the invention to the precise termsset forth. Although the invention has been described in detail withreference to certain illustrative embodiments, variations andmodifications exist within the scope and spirit of the invention asdescribed and defined in the following claims.

What is claimed is:
 1. A method of optimizing healthcare servicesconsumption, including the steps of: assessing a healthcare situation ofa population of patients that reside and consume healthcare services ina geographic zone, the geographic zone consisting of a plurality ofgeographic regions, each of which includes at least one of a residentialaddress of a patient in the population and a location of a provider whoservices patients in the population; using a computing device totransform information generated by the population into data representinga first group of patients from the population likely to have a higherconsumption of healthcare services than other patients in thepopulation; periodically determining whether patients in the first grouphave obtained healthcare services that satisfy predeterminedrequirements; using a computing device to transform information aboutproviders in the geographic zone into identification of a first group ofproviders in the geographic zone who provide high quality, costefficient healthcare services relative to other providers in thegeographic zone; prompting patients who have not obtained healthcareservices that satisfy the predetermined requirements to obtainadditional healthcare services to satisfy the predetermined requirementsfrom providers in the first group of providers; and communicating withpatients to urge the patients to obtain the healthcare services from aprovider in the first group of providers.
 2. The method of claim 1,wherein the assessing step includes the step of comparing costsassociated with healthcare services in the geographic zone with costs ofsimilar healthcare services in a geographic area that is larger than thegeographic region.
 3. The method of claim 1, wherein the assessing stepincludes accessing information describing healthcare data of healthcareconsumers in the geographic zone and healthcare consumers outside thegeographic zone.
 4. The method of claim 1, wherein the step of using acomputing device to transform healthcare information includes the stepof identifying patients suffering from at least one illness.
 5. Themethod of claim 1, wherein the step of using a computing device totransform healthcare information includes the step of assigning ahealthcare index to each patient based upon factors including age andgender of the patient.
 6. The method of claim 1, wherein the step ofusing a computing device to transform information about providersincludes the steps of identifying episodes of healthcare for each of theproviders in the geographic zone and comparing characteristics of theepisodes of healthcare with characteristics of similar episodes ofhealthcare associated with providers in a geographic area that is largerthan the geographic region.
 7. The method of claim 1, wherein the stepof using a computing device to transform information about providersincludes the steps of performing an individual calculation for eachprovider in the geographic zone to determine the provider's costefficiency index, and assigning a non-certified designation to eachprovider having cost efficiency index that fails to satisfy a firstpredetermined condition.
 8. The method of claim 7, wherein the step ofusing a computing device to transform information about providersincludes the steps of performing an individual analysis for eachprovider to determine the provider's service rating, and assigning anon-certified designation to each provider having a service rating thatfails to satisfy a second predetermined condition.
 9. The method ofclaim 8, wherein the step of determining a service rating for eachprovider includes the step of evaluating the number and types ofservices ordered by each provider for the treatment of a illness. 10.The method of claim 8, wherein the step of using a computing device totransform information about providers includes the steps of evaluatingthe practice patterns of each provider, and assigning a non-certifieddesignation to each provider having practice patterns that fail tosatisfy a third predetermined condition.
 11. The method of claim 10,wherein the step of using a computing device to transform informationabout providers includes the steps of assigning a qualified designationto each provider having a cost efficiency index, a service rating, andpractice patterns that satisfy the first, second, and thirdpredetermined conditions, respectively.
 12. The method of claim 1,wherein the prompting patients step includes the step of urging thepatients who have not obtained healthcare services that satisfy thepredetermined requirements to obtain additional healthcare services fromproviders in the first group of providers.
 13. The method of claim 1,wherein the prompting patients step includes the step of attempting tocontact the providers of the patients who have not obtained healthcareservices that satisfy the predetermined requirements in an effort topersuade the patients to obtain additional services.
 14. The method ofclaim 1, further including the steps of ranking the other providers inthe geographic zone based on an analysis of the quality and costefficiency of practice patterns associated with the other providers,dividing the ranking of providers into a second group of other providershaving a common characteristic and a third group of other providershaving a common characteristic.
 15. The method of claim 14, wherein thestep of ranking the other providers includes the step of assigning acost efficiency index to each of the other providers.
 16. The method ofclaim 14, wherein the step of ranking the other providers includes thestep of evaluating a practice pattern characteristic of each of theother providers.
 17. The method of claim 14, wherein the step ofcommunicating with patients includes the step of urging patients whohave obtained services from a third group provider to obtain futureservices from a second group provider.
 18. The method of claim 17,wherein the step of communicating with patients includes the step ofconducting a first set of intervention actions if the patient uses asecond group provider, the first set of intervention actionscorresponding to a first degree of involvement of a healthcare qualitymanagement representative in the provision of services by the secondgroup provider.
 19. The method of claim 18, wherein the step ofcommunicating with patients includes the step of conducting a second setof intervention actions if the patient uses a third group provider, thesecond set of intervention actions corresponding to a second degree ofinvolvement of the healthcare quality management representative in theprovision of services by the third group provider, the second degree ofinvolvement being greater than the first degree of involvement.
 20. Amethod of optimizing healthcare services consumption, including thesteps of: assessing a healthcare situation of a population that residesand consumes healthcare services in a geographic region; using acomputing device to transform past healthcare data generated by thepopulation into data representing a first group of patients likely tohave a higher consumption of healthcare services than other patients inthe population; periodically determining whether patients in the firstgroup have obtained healthcare services that satisfy predeterminedrequirements; using a computing device to transform data representingpast practice patterns of providers of healthcare services to thepatients into data representing a first group of providers in thegeographic region who provide high quality, cost efficient healthcareservices relative to other providers in the geographic region; promptingpatients who have not obtained healthcare services that satisfy thepredetermined requirements to obtain additional healthcare services tosatisfy the predetermined requirements from providers in the first groupof providers; determining whether a patient has obtained healthcareservices from a provider not in the first group of providers; andcontacting the patient to urge the patient to obtain healthcare servicesfrom a provider in the first group of providers.
 22. A method ofoptimizing healthcare services consumption of a patient population,including the steps of: transforming using a computing device past datagenerated by the patients into data representing a first group ofpatients likely to have a higher consumption of healthcare services thanother patients in the population; transforming using a computing devicepast practice patterns data of providers who provide services to thepatients into data representing a first group of providers who providehigh quality, cost efficient healthcare services relative to otherproviders of the patients; periodically determining whether patients inthe first group suffer from one or more conditions; determining whetherthe patients suffering from one or more conditions have obtainedhealthcare services that satisfy a predetermined set of minimum annualcare requirements (MACR) associated with the one or more conditions; andinitiating a communication with a patient who has not obtainedhealthcare services that satisfy the predetermined set of MACR toinstruct the patient to obtain additional healthcare services to satisfythe predetermined set of MACR from a provider in the first group ofproviders.
 23. A system for optimizing healthcare services consumptionof a patient population, including: a first computing device; a databasecoupled to the first computing device; and at least one additionalcomputing device coupled via a network to at least one of the firstcomputing device and the database that provides past data generated bythe patients and past practice patterns data of providers who provideservices to the patients for storage in the database; wherein the firstcomputing device includes software having instructions which, whenexecuted by the first computing device, causes the first computingdevice to transform the past data generated by the patients into datarepresenting a first group of patients likely to have a higherconsumption of healthcare services than other patients in thepopulation, transform the past practice patterns data into datarepresenting a first group of providers who provide high quality, costefficient healthcare services relative to other providers of thepatients, periodically determine whether patients in the first groupsuffer from one or more conditions, determine whether the patientssuffering from one or more conditions have obtained healthcare servicesthat satisfy a predetermined set of minimum annual care requirements(MACRs) associated with the one or more conditions, and generate areport identifying a patient who has not obtained healthcare servicesthat satisfy the predetermined set of MACRs to prompt communication withthe patient to instruct the patient to obtain additional healthcareservices to satisfy the predetermined set of MACRs from a provider inthe first group of providers.
 24. A system for optimizing healthcareservices consumption of a population of patients who receive servicesfrom providers, including: a first computing device; a database coupledto the first computing device; a second computing device coupled to thefirst computing device via at least one network; and a third computingdevice coupled to the first computing device via the at least onenetwork; wherein the first computing device receives patient informationabout the past health of the patients over the at least one network,stores the patient information in the database, and executes softwarewhich analyzes the patient information to identify a group of patientshaving a high likelihood of requiring healthcare services; wherein thefirst computing device receives provider information about the practicesof the providers, stores the provider information in the database, andexecutes software which analyzes the provider information to identify agroup of preferred providers; and wherein the first computing devicegenerates at least one report identifying the group of patients and thepreferred providers to facilitate attempts to contact a patient in thegroup to urge the patient to obtain future services from a preferredprovider.